Cardiac vagal tone, a non‐invasive measure of parasympathetic tone, is a clinically relevant tool in Type 1 diabetes mellitus

Brock, Christina; Jessen, Niels; Brock, Birgitte; Jakobsen, Poul Erik; Hansen, T K; Rantanen, Jukka; Riahi, Sam; Dimitrova, Yoanna Krasimirova; Dons-Jensen, Anna; Aziz, Qasim; Drewes, Asbjørn Mohr; Farmer, Adam D.

doi:10.1111/dme.13421

Cited by 34 publications

(30 citation statements)

References 29 publications

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“…Twenty‐four‐hour heart rate variability (HRV) was assessed (Impresario Software version 3; Spacelabs Healthcare Inc., Snoqualmie, WA, USA), deriving HRV indices from within 5‐minute cycles of R‐R‐intervals. The following time domain HRV indices were obtained: standard deviation of the averages of NN intervals in all 5‐minute segments of a 24‐hour recording, reflecting autonomic imbalance (both sympathetic and parasympathetic tone); and the root mean square of difference of successive normal R‐R intervals reflecting parasympathetic tone . In addition, fast Fourier transformation provided the following frequency domain HRV indices: derived total power, very low frequency, low frequency, high frequency and the low/high frequency ratio (reflecting sympatico–vagal balance).…”

Section: Methodsmentioning

confidence: 99%

“…Both cardiac vagal tone and cardiac sensitivity to the baroreceptor are real time measures of efferent and afferent brainstem influence on the heart (Neuroscope, MediFit Instruments, Enfield, Essex, UK). The complementarity of these measures in diabetes are described in detail elsewhere …”

Section: Methodsmentioning

confidence: 99%

“…Twenty-four-hour heart rate variability (HRV) was assessed (Impresario Software version 3; Spacelabs Healthcare Inc., Snoqualmie, WA, USA), deriving HRV indices from reflecting autonomic imbalance (both sympathetic and parasympathetic tone); and the root mean square of difference of successive normal R-R intervals reflecting parasympathetic tone. 18 In addition, fast…”

Section: Autonomic Neuronal Assessmentcardiometric Derived Autonomimentioning

confidence: 99%

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Liraglutide treatment reduced interleukin‐6 in adults with type 1 diabetes but did not improve established autonomic or polyneuropathy

Brock

Hansen

Karmisholt

et al. 2019

Brit J Clinical Pharma

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AimsType 1 diabetes can be complicated with neuropathy that involves immune‐mediated and inflammatory pathways. Glucagon‐like peptide‐1 receptor agonists such as liraglutide, have shown anti‐inflammatory properties, and thus we hypothesized that long‐term treatment with liraglutide induced diminished inflammation and thus improved neuronal function.MethodsThe study was a randomized, double‐blinded, placebo‐controlled trial of adults with type 1 diabetes and confirmed symmetrical polyneuropathy. They were randomly assigned (1:1) to receive either liraglutide or placebo. Titration was 6 weeks to 1.2–1.8 mg/d, continuing for 26 weeks. The primary endpoint was change in latency of early brain evoked potentials. Secondary endpoints were changes in proinflammatory cytokines, cortical evoked potential, autonomic function and peripheral neurophysiological testing.ResultsThirty‐nine patients completed the study, of whom 19 received liraglutide. In comparison to placebo, liraglutide reduced interleukin‐6 (−22.6%; 95% confidence interval [CI]: −38.1, −3.2; P = .025) with concomitant numerical reductions in other proinflammatory cytokines. However neuronal function was unaltered at the central, autonomic or peripheral level. Treatment was associated with −3.38 kg (95% CI: −5.29, −1.48; P < .001] weight loss and a decrease in urine albumin/creatinine ratio (−40.2%; 95% CI: −60.6, −9.5; P = .02).ConclusionHitherto, diabetic neuropathy has no cure. Speculations can be raised whether mechanism targeted treatment, e.g. lowering the systemic level of proinflammatory cytokines may lead to prevention or treatment of the neuroinflammatory component in early stages of diabetic neuropathy. If ever successful, this would serve as an example of how fundamental mechanistic principles are translated into clinical practice similar to those applied in the cardiovascular and nephrological clinic.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Autonomic Neuronal Assessmentcardiometric Derived Autonomimentioning

confidence: 99%

See 1 more Smart Citation

Liraglutide treatment reduced interleukin‐6 in adults with type 1 diabetes but did not improve established autonomic or polyneuropathy

Brock

Hansen

Karmisholt

et al. 2019

Brit J Clinical Pharma

Self Cite

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“…CVT is measured on a linear vagal scale (LVS), where a value of 0 is derived from fully atropinized healthy human volunteers [Julu, ; Julu and Hondo, ]. CVT has been demonstrated to closely correlate ( r > 0.75, P < 0.0001) with more traditional measures of HRV, including those derived from frequency domain analysis [Brock et al, ].…”

Section: Methodsmentioning

confidence: 99%

Morphology of subcortical brain nuclei is associated with autonomic function in healthy humans

Ruffle

Coen

Giampietro

et al. 2017

Human Brain Mapping

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The autonomic nervous system (ANS) is a brain body interface which serves to maintain homeostasis by influencing a plethora of physiological processes, including metabolism, cardiorespiratory regulation and nociception. Accumulating evidence suggests that ANS function is disturbed in numerous prevalent clinical disorders, including irritable bowel syndrome and fibromyalgia. While the brain is a central hub for regulating autonomic function, the association between resting autonomic activity and subcortical morphology has not been comprehensively studied and thus was our aim. In 27 healthy subjects [14 male and 13 female; mean age 30 years (range 22-53 years)], we quantified resting ANS function using validated indices of cardiac sympathetic index (CSI) and parasympathetic cardiac vagal tone (CVT). High resolution structural magnetic resonance imaging scans were acquired, and differences in subcortical nuclei shape, that is, 'deformation', contingent on resting ANS activity were investigated. CSI positively correlated with outward deformation of the brainstem, right nucleus accumbens, right amygdala and bilateral pallidum (all thresholded to corrected P < 0.05). In contrast, parasympathetic CVT negatively correlated with inward deformation of the right amygdala and pallidum (all thresholded to corrected P < 0.05). Left and right putamen volume positively correlated with Additional Supporting Information may be found in the online version of this article. CVT (r 5 0.62, P 5 0.0047 and r 5 0.59, P 5 0.008, respectively), as did the brainstem (r 5 0.46, P 5 0.049). These data provide novel evidence that resting autonomic state is associated with differences in the shape and volume of subcortical nuclei. Thus, subcortical morphological brain differences in various disorders may partly be attributable to perturbation in autonomic function. Further work is warranted to investigate these findings in clinical populations. Hum Brain Mapp 39:381-392, 2018.

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“…Moreover, mathematically CVT correlates closely to other putative ‘parasympathetic’ measures, including both HRV and root mean square of successive differences (RMSSD) (Brock et al . ).…”

Section: Methodsmentioning

confidence: 97%

Functional brain networks and neuroanatomy underpinning nausea severity can predict nausea susceptibility using machine learning

Ruffle

Patel

Giampietro

et al. 2019

The Journal of Physiology

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Key points Nausea is an adverse experience characterised by alterations in autonomic and cerebral function. Susceptibility to nausea is difficult to predict, but machine learning has yet to be applied to this field of study. The severity of nausea that individuals experience is related to the underlying morphology (shape) of the subcortex, namely of the amygdala, caudate and putamen; a functional brain network related to nausea severity was identified, which included the thalamus, cingulate cortices (anterior, mid‐ and posterior), caudate nucleus and nucleus accumbens. Sympathetic nervous system function and sympathovagal balance, by heart rate variability, was closely related to both this nausea‐associated anatomical variation and the functional connectivity network, and machine learning accurately predicted susceptibility or resistance to nausea. These novel anatomical and functional brain biomarkers for nausea severity may permit objective identification of individuals susceptible to nausea, using artificial intelligence/machine learning; brain data may be useful to identify individuals more susceptible to nausea. Abstract Nausea is a highly individual and variable experience. The central processing of nausea remains poorly understood, although numerous influential factors have been proposed, including brain structure and function, as well as autonomic nervous system (ANS) activity. We investigated the role of these factors in nausea severity and if susceptibility to nausea could be predicted using machine learning. Twenty‐eight healthy participants (15 males; mean age 24 years) underwent quantification of resting sympathetic and parasympathetic nervous system activity by heart rate variability. All were exposed to a 10‐min motion‐sickness video during fMRI. Neuroanatomical shape differences of the subcortex and functional brain networks associated with the severity of nausea were investigated. A machine learning neural network was trained to predict nausea susceptibility, or resistance, using resting ANS data and detected brain features. Increasing nausea scores positively correlated with shape variation of the left amygdala, right caudate and bilateral putamen (corrected P = 0.05). A functional brain network linked to increasing nausea severity was identified implicating the thalamus, anterior, middle and posterior cingulate cortices, caudate nucleus and nucleus accumbens (corrected P = 0.043). Both neuroanatomical differences and the functional nausea‐brain network were closely related to sympathetic nervous system activity. Using these data, a machine learning model predicted susceptibility to nausea with an overall accuracy of 82.1%. Nausea severity relates to underlying subcortical morphology and a functional brain network; both measures are potential biomarkers in trials of anti‐nausea therapies. The use of machine learning should be further investigated as an objective means to develop models predicting nausea susceptibility.

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Cardiac vagal tone, a non‐invasive measure of parasympathetic tone, is a clinically relevant tool in Type 1 diabetes mellitus

Abstract: Cardiac vagal tone represents a convenient, clinically relevant method of assessing parasympathetic nervous system tone, potentially facilitating the earlier identification of people with Type 1 diabetes who should undergo formal autonomic function testing.

Cited by 34 publications

References 29 publications

Liraglutide treatment reduced interleukin‐6 in adults with type 1 diabetes but did not improve established autonomic or polyneuropathy

Liraglutide treatment reduced interleukin‐6 in adults with type 1 diabetes but did not improve established autonomic or polyneuropathy

Morphology of subcortical brain nuclei is associated with autonomic function in healthy humans

Functional brain networks and neuroanatomy underpinning nausea severity can predict nausea susceptibility using machine learning

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